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The subject is designed for all students in bachelor programmes, especially aimed at economics. Students learn basic notions and algorithms in mathematical optimization.
Last update: Kubová Petra (01.05.2019)
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General skills: 1. basic terms in mathematical optimiztion 2. knowledge and understanding of basic algorithms 3. individual problem solving 4. basic mathematical background for formulation and solving of optimization problems 5. numerical algorithms . Last update: Kubová Petra (01.05.2019)
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A: Dimitris Bertsimas and John N. Tsitsiklis : Introduction to Linear Optimization, 1997, ISBN-10: 1-886529-19-1 A: Alexander Schrijver : Theory of Linear and Integer Programming, New York 1986, ISBN-10: 0471982326 Last update: MAXOVAJ (20.01.2020)
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Lectures and seminars
Last update: Kubová Petra (01.05.2019)
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1. Problems of mathematical optimization. 2. Linear programming. 3. Convex polyhedra. 4. Simplex method. 5. Duality of linear programming. 6. Integer programming, totally unimodular matrices. 7. Basic notions of graph theory. 8. Shortest path problem. 9. Tree, spanning tree, greedy algorithm. 10. Discrete optimalization problems as problems of integer programming. 11. Nonlinear optimization. 12. Kuhn-Tucker conditions. 13. Numerical methods for nonlinear programming. 14. Convex functions, positive semidefinite matrices. Last update: MAXOVAJ (17.01.2020)
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http://www.vscht.cz/mat/ZMO/Optim_maple.html https://iti.mff.cuni.cz/series/2006/311.pdf Last update: MAXOVAJ (20.01.2020)
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Mathematics A, Mathematics B (or Mathematics I, Mathematics II) Last update: MAXOVAJ (20.01.2020)
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Teaching methods | ||||
Activity | Credits | Hours | ||
Účast na přednáškách | 1 | 28 | ||
Příprava na přednášky, semináře, laboratoře, exkurzi nebo praxi | 0.5 | 14 | ||
Práce na individuálním projektu | 1 | 28 | ||
Příprava na zkoušku a její absolvování | 1.5 | 42 | ||
Účast na seminářích | 1 | 28 | ||
5 / 5 | 140 / 140 |